Role Overview
Mercor is partnering with leading AI labs on Project Atlas — an initiative to build realistic enterprise environments that frontier AI agents are trained and evaluated in. We're seeking experienced materials-science professionals from Fortune 500 R&D organizations, major national labs, and top R1 universities (e.g., Corning, 3M, DuPont, Dow, Intel, Applied Materials, national labs, leading materials-science departments) to recreate the digital workspaces they run every day and design the tasks that genuinely challenge state-of-the-art AI.
You'll bring your expertise in materials R&D, characterization, process development, or reliability engineering to build a high-fidelity environment that mirrors the tools, files, and workflows of a serious materials-science organization — and then author tasks grounded in the programs you actually run today.
Key Responsibilities
- Build a realistic digital workspace centered on the Drive folders you use day-to-day — the experimental write-ups, characterization reports, simulation results, technology transfer memos, IP disclosures, project proposals, and email threads that reflect how you actually organize your work — with some representation of the platforms that support it (e.g., VASP or Materials Studio (Biovia), LabVantage LIMS, ANSYS Fluent)
- Design multi-step tasks grounded in your real workflows that require navigating multiple apps, files, and stakeholders in a way that meaningfully challenges frontier AI agents
- Collaborate with other materials-science experts in your field to design the environment, shape task scope, and review each other's scenarios for realism and rigor
- Work asynchronously with research teams to refine task designs and evaluation criteria for materials-science agent benchmarks
- Contribute to frontier AI research and benchmarking — the work you produce directly informs how leading labs train and evaluate the next generation of AI systems
Ideal Qualifications
- MS / PhD in materials science, chemistry, physics, or related discipline
- 3+ years of full-time experience at a Fortune 500 R&D organization, national lab, or R1 university materials research group
- Background in one or more areas such as:
- Metals, polymers, ceramics, composites, or semiconductor materials
- Characterization (XRD, SEM/TEM, spectroscopy, thermal analysis)
- Computational materials science / DFT / MD
- Process development and scale-up
- Reliability / failure analysis in advanced materials
- Day-to-day use of VASP / Materials Studio (Biovia), LabVantage / LabWare LIMS, and ANSYS Fluent / STAR-CCM+
- Strong analytical thinking and writing — able to translate materials-science workflows into structured task specs
Compensation Note
This project is expected to begin on an effective hourly rate, but will transition to a model where experts are compensated based on throughput of quality work rather than a flat accruing hourly rate.
About Mercor
Mercor is a talent marketplace that connects top experts with leading AI labs and research organizations. Backed by investors including Benchmark, General Catalyst, Adam D'Angelo, and Jack Dorsey. Thousands of professionals across domains contribute to projects shaping the next generation of AI systems.